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This study aims to determine and analyze farmers’ risk perceptions and risk management strategies in agricultural production. Data were obtained in 2015 production year from face-to-face interviews of 99 farmers in Yüregir and Karaisalı district of Adana province of Turkey. Factor analysis was used in data reduction to identify a small number of factors related to risk sources and risk strategies in this study. Then, multiple regression model was used to evaluate the influence of socioeconomic characteristics on the farmers’ risk perceptions and risk management strategies using factor loadings. The results of this study show that the most important risk source that the farmers' perceive is availability of many middlemens in agriculture and food market and risk management strategy that the farmers' perceive is producing at the lowest cost. The result of factor analysis showed that the risk scale consists of 5 factors explaining 60.66% of total variance. The internal consistency coefficient Cronbach Alfa of the scale is 0.918 and KMO is 0.869. The risk management scale consists of 4 factors explaining 64.23% of total variance. The internal consistency coefficient Cronbach Alfa of the scale is 0.944 and KMO is 0.910. According to the results, perceptions are farmer-specific, a number of socio-economic variables are found to be related to risk and risk management. Improving of risk management strategies is useful for farmers as well and might help them to avoid many risks and reduce losses.

Tez (Yüksek Lisans) -- Çukurova Üniversitesi, Adana, 1996. Kaynakça (s. 85-97) var. xvi, 99 s. ; 30 cm. TEZ2025 …

In this study, various estimations and analyses are used on the basis of sand amount in soil texture using popular artificial intelligence methods like linear regression, artificial neural network and adaptive neuro fuzzy inference system. Clay, silt and sand, which form the inorganic texture of the soil, are settled in the water with different speeds due to their density differences. Based on this point, using the density difference of moving particles through a mixed soil and water suspension, estimations are made on specific soil samples’ data. The sand particle is the biggest particle among the others in terms of volume, it can be measured by simple tools and can produce more scalable results. The accuracy of the estimations, which are made with frequently used methods in machine learning like linear regression, artificial neural network and adaptive neuro fuzzy inference system, are inspected in details using the magnitude change of the light passing through the beaker due to differentiation of density by time. Details of the analyses and estimations, which can be used to determine the approximate sand amount in soil and in situations that don’t require sensitive measuring, are compared with each other in details. Also the possibility of making a mobile measurement device using this setup which is built with cheap and easy-tofind equipment is discussed. Bu çalışmada, doğrusal regresyon, yapay sinir ağı ve uyumlu sinirsel-bulanık çıkarım sistemi gibi popüler yapay zeka metodları kullanılarak toprak bünyesinin kum ihtivası üzerine çeşitli analiz ve tahminlemeler yapılmıştır. Toprağın inorganik yapısını oluşturan kil, silt ve kum tanecikleri, yoğunluk farklarından dolayı su içerisinde farklı hızlarda çökelmektedirler. Bu noktadan yola çıkılarak bir beher içerisinde hazırlanan su ve toprak solüsyonundaki parçacıkların, farklı hızlarda çökelme özelliklerinden faydalanılarak toprak örneğindeki kum miktarı üzerine tahminlemeler yapılmıştır. Parçacıklar arasındaki en iri tanecikli yapı kum olduğundan basit teçhizatlar ile daha kolay gözlemlenebilir ve işlenebilir sonuçlar üretmektedir. Beherden geçirilen ışığın şiddetinin kumun çökelmesi sonucu değişimiyle elde edilen işaret serileri regresyon, ANN ve ANFIS gibi makine öğrenmesinde sıkça kullanılan methodlar ile işlenerek yapılan tahminlemelerin tutarlılığı incelenmiştir. Kabaca kum tayini gerektiren ve çok hassas ölçümlemeler gerektirmeyen durumlarda kullanılabilecek analiz ve tahminleme yöntemlerinin başarıları detaylı olarak karşılaştırılmıştır. Kolay ve ucuz bulunabilen araçlar kullanılarak oluşturulan bu düzenek ile, çıkan sonuçların başarıları da hesaba katılarak, mobil bir ölçümleme cihazının uygulanabilirliği de tartışılmıştır. Tez (Yüksek Lisans) -- Çukurova Üniversitesi, Adana, 2016. xi, 77 s. : res., tablo ; 29 cm. Kaynakça (s. 61-67) var. TEZ10009

Herbisit direnci, herbisitlerin yoğun bir şekilde kullanımından kaynaklanmış olup, son yıllarda tarım ve gıda güvencesini tehdit eden küresel bir sorun haline gelmiştir. ACCase ve ALS inhibitörlerine dirençli olan yabancı otlar, dünya genelinde bildirilen tüm direnç vakalarının üçte birinden fazlasını oluşturur ve Akdeniz çevrelerde buğday üretiminin ana kısıtlayıcısı olmaktadır. Ancak, yabancı otlardaki herbisit direncini saptamak için farklı yaklaşımlar geliştirilmiştir. Bu çalışma, Adana ilinde yetişen Kısır Yabani Yulaf (Avena. sterilis)’taki Asetil CoA Karboksilaz (ACCase) ve asetolaktat sentetaz (ALS) inhibe eden herbisitlere karşı direnci saptamak amacıyla kullanılan hızlı testler [flitre kağdı ve agar bazlı (tohum ve fide)], sera test ve moleküler testlerinin güvenilirliği ve geçerliliği karşılaştırılmasını amaçlanmıştır. Moleküler testlerde, dirençli ve hassas popülasyonlarının ACCase genleri dizilmiş ve karşılaştırılmıştır. Yapılan çalışmada, sera testleri, dirençli A. sterilis popülasyonunun clodinafop-propargyl (11.97 kat) ve pyroxsulam (42.88 kat)'a karşı yüksek bir direnç seviyesine; ve pinoxaden (2.1 kat) ve mesosulfuron-methyl iodosulfuron-methylsodium (1.08 kat)'e karşı düşük bir direnç seviyesine sahip olduğunu doğrulamıştır. Hızlı testlerden elde edilen direnç seviyelerinin tüm herbisitlerde 5 kattan az olduğu bulunmuştur. ACCase geninde altı mutasyon noktası ""Serin (Ser), Glisin (Gly), Treonin (Thr), Valin (Val), Glutamin (Gln) ve Fenilalanin (Phe)"""" tespit edilmiştir. Sonuç olarak, agar bazlı testler, doğru, hızlı ve uygun maliyetli herbisit direnci onayları sağlayıp, sera ve flitre kağdı testlerine göre daha az alana ihtiyaç duymaktadır. Moleküler testi, dirençli popülasyondaki hedef bölge direncini doğrulamıştır. Çalışma, bu mutasyonları Türkiye'de ilk kez A. sterilis’te rapor etmektedir. Intensive use of herbicides has resulted in the occurrence of herbicide resistance. Recently, herbicide resistance has become a global issue threatening agricultural food production. ACCase and ALS-inhibitor-resistant weeds constitute more than one-third of all the reported resistance cases worldwide becoming the main constraint to wheat production in Mediterranean environments. However, different techniques have been devised to detect herbicide resistance in weeds. This study was aimed to compare the reliability and validity of quick tests [filter paper and agar-based (seed and seedling)], greenhouse (whole-plant pot) and molecular tests for detecting the resistance to acetyl-CoA carboxylase (ACCase) and acetolactate synthase (ALS)-inhibiting herbicides in sterile wild oat (Avena sterilis L.) in Adana, Turkey. In the molecular test, ACCase genes of the resistance and susceptible populations were sequenced and compared. As a result, greenhouse tests confirmed that the resistant population of A. sterilis has a high-level of resistance to clodinafop-propargyl (11.97 fold) and pyroxsulam (42.88 fold); and low resistance level to pinoxaden (2.1 fold) and mesosulfuronmethyl+ iodosulfuron-methyl-sodium (1.08 fold). The levels of resistance obtained from quick tests were less than 5-folds in all herbicides. Six mutation points ""Serine (Ser), Glycine (Gly), Threonine (Thr), Valine (Val), Glutamine (Gln) and Phenylalanine (Phe)"" were detected in the ACCase gene. In conclusion, the agar-based tests provided feasible, accurate, rapid and costeffective herbicide resistance confirmations which need less space than a greenhouse and filter paper tests. The molecular test confirmed the target-site resistance in the resistant population. The study reports these mutations for the first time in A. sterilis in Turkey. Tez (Doktora) -- Çukurova Üniversitesi, Adana, 2019. xxv, 113 s. : res. (bzs. rnk.), tablo ; 29 cm. Kaynakça (s. 85-111) var. TEZ12003

Küresel Değer Zincirleri (KDZ) Afrikalı küçük çiftçilerin dünya pazarlarına girmesi için fırsatlar yaratabileceği gibi onların dünya pazarlarından dışlanması riskini de yaratabilir. Bu çalışmada, seçilmiş Afrika ülkeleriyle ilgili mevcut veriler ve literatür gözden geçirilerek Afrika tarımının KDZ içerisindeki rolü irdelenmiştir. Dünyanın diğer bölgelerine nazaran Afrika KDZ ile daha derin ilişkiler içerisine girmiştir. Bununla birlikte tüm bulgular Afrika tarımının KDZ içindeki yerinin hâlâ zincirin başlarında, dünyaya hammadde temin eden bir konumda donup kaldığını, katma değerin ise kıta dışında gerçekleştirildiği bilgisini pekiştirmektedir. Benzer şekilde piyasalar baskın bir şekilde, doğrudan veya dolaylı olarak, hâlâ büyük firmalar veya onların yerel temsilcileri tarafından yönetilmektedir. Afrika’nın karşılaştığı yetersiz altyapı ve yatırımlar, mali imkânsızlıklar, düşük girdi kullanımı ve düşük verimlilikler gibi problemler nedeniyle zincirde daha ileri noktalara yükselme olanakları kısıtlıdır. Afrika ülkeleri uzun vadede bu güçlüklerin üstesinden gelmek zorundadır. Fakat yine de bu ülkeler kısa vadede organik ve niş piyasalara ürünler üreterek bazı dezavantajlarını (yoğun emek kullanımı, az girdi kullanımı ve henüz tarıma açılmamış geniş alanlar vb.) KDZ içerisinde avantajlara dönüştürebilirler. Global Value Chains (GVCs) may create opportunities for African small farmers to enter international markets but also risks of being excluded from the world markets. This study evaluates African agriculture within the GVCs by reviewing available agricultural data and GVC literature on selected African countries. Africa is deeply involved in GVCs more than many regions around the world. However, the overall finding of this study consolidates the fact that African agriculture in the GVCs is still stagnated in the upstream role providing raw agricultural products to the world where value addition is being carried out outside the continent. Similarly, markets are still dominated by big companies and firms either directly or through their local agents in Africa. Upgrading within GVCs is limited due to multiple problems facing Africa, such as lack of infrastructure, financial deficiencies, insufficient investments, low input use and low efficiencies. African countries should overcome these difficulties in the long run. However, they may manage to turn some of the disadvantages (labor use intensity, less chemical use and large areas yet not opened to agriculture, etc.) into advantages in the GVCs by producing organic products and addressing niche markets in the short run. Tez (Yüksek Lisans) -- Çukurova Üniversitesi, Adana, 2020. XV, 111 s. :_res. (bzs. rnk.), tablo ;_29 cm. Kaynakça (s. 99-109) var. TEZ12815

In laboratory bioassay, the traditionally prepared unrefined oil from mustard and water mixture (50% concentration) and different layers of this mixture were applied to yellow starthistle seeds (Centaurea solstitialis L.). The results indicated that, three layers (upper, middle and lower) of mustard oil + water mixture significantly reduced the germination of yellow starthistle. There was complete inhibition of germination in upper and middle layers of mustard oil + water mixture added to petri dishes. The mixtures (20% and 40% concentration) were applied as pre- emergence and post-emergence sprays on plants in greenhouse condiditons. There was no effect of pre-emergence application on the emergence of yellow starthistle seedlings. However, pre- emergence application, (1 or 2 sprays) of upper layer of 40 % mixture reduced the plant height, fresh and dry mass of yellow starthistle. This study showed the allelopathic effects of mustard oil+water mixture on this weed. It could be used in organic crop production, where yellow starthistle is problem or combined with other management methods.

This study looks at research carried out on soils of the Denizli Province (Western Turkey). The study area is under very intensive agricultural usage. There are large agricultural areas at present but, in the future, farmers can't find suitable field for their agricultural activity because of increasingly widespread non-agricultural utilizations. Soil characteristics, detailed soil map, soil classification and Land Capability Classes (LCC) studies were carried out for this research. Based on remote sensing data and GIS, 58 soil series were identified on 8 physiographic units by field survey and they were classified in 4 soil orders as Entisols, Inceptisols, Mollisols and Vertisols. Distributions of the soil orders are 41, 12, 8 and 39% of the studied area, respectively. Four widespread physiographic units were identified as lake (terrace, bottom, skirt), clay deposit, alluvial fan (top, central, end) and alluvial terrace. Each of these units take up 26, 25.1, 15.9 and 10.6% of the area, respectively. Agricultural (I, II, III and IV classes of the LCC) and non-agricultural areas (V, VI, VII and other usages) were identified in proportions as 88.7% and 11.3%, respectively.

In this article, a method was developed to be used in determining and evaluation of the existing urban green areas from the ecological point of view. To this extent, Normalised Difference Vegetation Index (NDVI) values of urban parks were used as the ecological indicator. Vegetation cover size and temporal growing rates in three parks with different size in Ankara City were determined by using Remote Sensing Technology. It was stated that although total vegetated areas in the parks were less than total park layouts, this expression is not itself enough in disclosing real plant's assets in the parks due to structural and phonological changes of the plants in course of time. This statement was demonstrated in studied parks in this paper and it was seen that, vegetation cover amount of the parks in different sizes could be equal to each other. Therefore, vegetation cover amount should be taken under consideration both temporally and spatially in determining and evaluation as well as monitoring of green areas in urban parks independent from external borders of the parks. NDVI is an important indicator to compare the effects of ecological value of different parks.

The aim of this study was to compare percent tree cover products of Envisat MERIS and MODIS data of Seyhan River Basin at the Eastern Mediterranean Region of Turkey. In this study, Regression Tree (RT) algorithm was used to estimate percent tree cover maps. This technique is well suited for percentage tree cover mapping because, as a non-parametric classifier, it requires no prior assumptions about the distribution of the training data. This model also allows for the calibration of the model along the entire continuum of tree cover, avoiding the problems of using only end members for calibration.The medium resolution Envisat MERIS with a 300 m and MODIS with a 500 m pixel representation data were used as predictor variables. Three scenes of high resolution IKONOS images were employed as a training data, and testing the accuracy of model. The regression tree method for this study consisted of six steps: i) generate reference percentage tree cover data, ii) derive metrics from Envisat MERIS and MODIS data, iii) select predictor variables, iv) fit RT model, v) undertake accuracy assessment and produce final model and map, vi) compare results. The training data set was derived supervised land cover classification of IKONOS imagery to generate reference percent tree cover data. Specifically, this classification was aggregated to estimate percent tree cover at the MERIS and MODIS spatial resolution.The predictor variables incorporated the MERIS and MODIS wavebands in addition to biophysical variables estimated from the MERIS and MODIS data. Percent tree cover maps were derived from MERIS and MODIS data for Seyhan upper Basin as final outputs. These final outputs consisted of spatially distributed estimates of percent tree cover at 300 m and 500 m spatial resolution and error estimates obtained through validation. This study showed that Envisat MERIS data can be used to predict percentage tree cover with greater spatial detail than using MODIS data. This finer-scale depiction should be of great utility for environmental monitoring purposes at the regional scale. © 2008 International Society for Photogrammetry and Remote Sensing. All rights reserved. 21st International Congress for Photogrammetry and Remote Sensing, ISPRS 2008 --3 July 2008 through 11 July 2008 -- --